This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Lafora disease (LD) is caused by mutations in the carbohydrate phosphatase laforin. A hallmark of LD is the accumulation of insoluble carbohyrate, called Lafora bodies (LBs), in the cytoplasm of cells. While LBs accumulate in most cells, apoptosis only occurs in neurons and this eventually leads to epilepsy and death of the patient. Wolff-Parkinson-White (WPW) syndrome is a cardiac hypertrophy caused by insoluble carbohydrate accumulations resulting from mutations in the cellular energy sensor and regulator AMP-activated protein kinase (AMPK). We recently identified both a phenotypic and biochemical connection between LD and WPW. We discovered that i) carbohyrate accumulations in LD and WPW are very similar, ii) laforin contains an AMPK consensus phosphorylation site, iii) AMPK phosphorylates laforin in vitro, and iv) carbohydrates increase AMPK kinase activity towards laforin. This proposal will define these events and determine the connection between LD and WPW. Specific Aim 1 will identify the conditions that promote phosphorylation in vivo and map the in vivo phosphorylation site(s). In specific Aim 2, we will determine if AMPK phosphorylation affects laforin binding to known substrates, the localization of laforin, and/or the phosphatase of laforin. In specific aim 3, we will determine the mechanism of carbohydrate stimulated AMPK kinase activity. In doing so, we will define the fold increase in AMPK-kinase activity, the carbohydrate(s) catalyst, and the substrates affected. Finally, we will translate these findings into a mouse model of LD. The studies proposed will define the connection between AMPK-WPW with laforin-LD. In addition, they will better characterize carbohydrate metabolism, which is at the heart of multiple metabolic disorders including diabetes, and yield insights into novel treatments.